股海罗盘 - A股股票量化分析

Stock Compass aims to address common decision-making pain points for A-share investors: when faced with numerous technical indicators and research report opinions, it is difficult to judge their historical effectiveness, often leading to the dilemma of "buying at the peak" or "selling at the bottom." Through its self-learning quantitative engine, it conducts over 600,000 historical signal backtests for each stock, attaching a clear historical match rate progress bar to each analysis signal, making "past accuracy" immediately apparent.

Users simply need to input a stock code or name to obtain 17-dimensional comprehensive data at once, including market quotes, capital flows, technical indicators, financials, holdings, share unlock events, research reports, and more. The system automatically performs ETF four-quadrant linkage analysis, multi-source fund flow cross-validation, and full-market brokerage research report coverage statistics, uncovering five types of pattern maps such as support/resistance levels and post-rise/fall probabilities, and generates a DOCX analysis report with K-line charts in one click.

This tool is particularly suitable for quantitative traders, data analysts requiring in-depth research and decision support, and investors with research needs in the A-share market. It transforms fragmented, subjective market information into structured quantitative conclusions supported by historical data.

It is recommended that users treat it as an auxiliary verification tool for investment decisions, not the sole basis. When using it, focus on signal patterns with high historical match rates and conduct multi-dimensional cross-validation in conjunction with the generated pattern maps. The automatically generated reports can serve as archival material or for client communication, but their conclusions should still be integrated with the latest market dynamics for comprehensive judgment.